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High Dimensional Probability VII - The Cargese Volume (Hardcover, 1st ed. 2016): Christian Houdre, David M. Mason, Patricia... High Dimensional Probability VII - The Cargese Volume (Hardcover, 1st ed. 2016)
Christian Houdre, David M. Mason, Patricia Reynaud-Bouret, Jan Rosinski
R4,879 R3,668 Discovery Miles 36 680 Save R1,211 (25%) Ships in 12 - 17 working days

This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Etudes Scientifiques de Cargese (IESC) in Corsica, France. High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.

High Dimensional Probability VII - The Cargese Volume (Paperback, Softcover reprint of the original 1st ed. 2016): Christian... High Dimensional Probability VII - The Cargese Volume (Paperback, Softcover reprint of the original 1st ed. 2016)
Christian Houdre, David M. Mason, Patricia Reynaud-Bouret, Jan Rosinski
R2,846 Discovery Miles 28 460 Ships in 10 - 15 working days

This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Etudes Scientifiques de Cargese (IESC) in Corsica, France. High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.

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